EP0242109A2 - Parallel computation network - Google Patents

Parallel computation network Download PDF

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Publication number
EP0242109A2
EP0242109A2 EP87303018A EP87303018A EP0242109A2 EP 0242109 A2 EP0242109 A2 EP 0242109A2 EP 87303018 A EP87303018 A EP 87303018A EP 87303018 A EP87303018 A EP 87303018A EP 0242109 A2 EP0242109 A2 EP 0242109A2
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Prior art keywords
amplifier
input
conductance
network
amplifiers
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EP87303018A
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German (de)
French (fr)
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EP0242109A3 (en
EP0242109B1 (en
Inventor
John Stewart Denker
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AT&T Corp
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American Telephone and Telegraph Co Inc
AT&T Corp
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    • GPHYSICS
    • G11INFORMATION STORAGE
    • G11CSTATIC STORES
    • G11C7/00Arrangements for writing information into, or reading information out from, a digital store
    • G11C7/06Sense amplifiers; Associated circuits, e.g. timing or triggering circuits
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/06Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
    • G06N3/063Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means
    • G06N3/065Analogue means

Definitions

  • Superior performance is achieved by equalizing the time constants of amplifiers used in highly parallel computational networks.
  • One technique employs a feedback arrangement where the resistance between the input of each amplifier i and ground, and the capacitor between the input of each amplifier and ground are instead connected in parallel between the input of each amplifier and its corresponding output.
  • a second technique employs a balanced impedance arrangement where, for example, a zero current with a non-zero thevenin conductance is achieved by employing equal valued T+ and Tij conductances.

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
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  • Life Sciences & Earth Sciences (AREA)
  • Biomedical Technology (AREA)
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  • Theoretical Computer Science (AREA)
  • Evolutionary Computation (AREA)
  • General Engineering & Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Artificial Intelligence (AREA)
  • General Health & Medical Sciences (AREA)
  • Molecular Biology (AREA)
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  • Computational Linguistics (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Neurology (AREA)
  • Amplifiers (AREA)
  • Hardware Redundancy (AREA)
  • Measurement Of Resistance Or Impedance (AREA)

Abstract

Superior performance is achieved by equalizing the time constants of amplifiers used in highly parallel computational networks. In accordance with one aspect of the invention a feedback arrangement is employed where the prior art resistance (FIG. 2, 22) between the input of each amplifier i and ground, and the capacitor (31) between the input of each amplifier and ground are instead connected in parallel between the input of each amplifier and its corresponding output. In accordance with another aspect of the invention a balanced impedance arrangement (FIG. 3) is employed where, for example, a zero current with a non-zero thevenin conductance is achieved by employing equal valued T
Figure imga0001
j and T

Description

    Background of the Invention
  • This relates to apparatus for parallel processing of signals.
  • Recently, advances in the computational circuits art have brought to the forefront a class of highly parallel computation circuits that solve a large class of complex problems in analog fashion. These circuits comprise a plurality of amplifiers having a sigmoid transfer function and a resistive feedback network that connects the output of each amplifier to the input of the other amplifiers. Each amplifier input also includes a capacitor connected to ground and a conductance connected to ground which may or may not include a capacitor and a conductor in addition to the parasitic capacitance and conductance. Input currents are fed into each amplifier input, and output is obtained from the collection of output voltages of the amplifiers.
  • A generalized diagram of this circuit is shown in FIG. 1, depicting amplifiers 10, 11, 12, 13 and 14 with positive and negative outputs V,, V2, V3, V., and VN, respectively. Those outputs are connected to an interconnection block 20 which has output lines 41-45 connected to the input ports of amplifiers 10-14, respectively. Within interconnection block 20, each output voltage Vi is connected to each and every output line of block 20 through a conductance (e.g., resistor). For convenience, the conductance may be identified by the specific output line (i.e., source) that is. connected by the conductance to a specific voltage line. For example, T
    Figure imgb0001
    identifies the conductance that connects the non-inverting output V2 to the input of the first amplifier (line 41).
  • Also connected to each amplifier input port is a parallel arrangement of a resistor and a capacitor (with the second lead of the resistor and capacitor connected to ground), and means for injecting a current into each input port (from some outside source).
  • Applying Kirchoffs current law to the input port of each amplifier i of FIG. 1 yields the equation:
    Figure imgb0002
    where
    • Ci is the capacitance between the input of amplifier i and ground,
      Figure imgb0003
    • is the equivalent resistance and it equals
      Figure imgb0004
      , where pi is the resistance between the input of amplifier i and ground, Ui is the voltage at the input of amplifier i,
    • T
      Figure imgb0005
      j is the a conductance between the non-inverting output of amplifier j and the input of amplifier i,
    • Tij is the a conductance between the inverting output of amplifier j and the input of amplifier i, Vi is the positive output voltage of amplifier j, related to Ui by the equation Vi = gi(Uj), and I i is the current driven into the input port of amplifier i by an external source. When
      Figure imgb0006
      may for convenience be expressed as Tij, and it is well known that a circuit satisfying equation (1) with symmetric Tij terms is stable. It is also well known that such a circuit responds to applied stimuli, and - reaches a steady state condition after a short transition time. At steady state, dui/dt = 0 and dV/dt = 0.
  • With this known stability in mind, the behavior of other functions may be studied which relate to the circuit of FIG. 1 and involve the input signals of the circuit, the output signals of the circuit, and/or the circuit's internal parameters.
  • Indeed, a function was studied that has the form
    Figure imgb0007
    where gi I (v) is a function that is related to the gain of the emplifiers and is such that the integral of the function
    • gr (V) approaches 0 as the gain of amplifier i approaches infinity. Also, the time derivative of the function E is negative, and that it reaches 0 when the time derivative of voltages V; reaches 0. Since equation (1) assures the condition of dVi /dt approaching 0 for all i, the function E of equation (2) is assured of reaching a stable state. The discovery of this function E led to the use of the FIG. 1 circuit in problem solving applications in associative memory applications, and in decomposition problems.
  • The FIG. 1 circuit can solve problems which can be structured so that the function to be minimized has at most second order terms in some parameters of the problem to permit correspondence to Equation (2). Other problems, however, may require the minimization of equations that contain terms of order higher than two. Those problems are solvable through the use of interneuron amplifiers wherein the
    Figure imgb0008
    are conductances that assume different values, which are a function of the problem to be solved. The different values, however, cause the circuit to behave differently in response to different stimuli because of the different time constants associated with each amplifier.
  • Summary of the Invention
  • Superior performance is achieved by equalizing the time constants of amplifiers used in highly parallel computational networks. One technique employs a feedback arrangement where the resistance between the input of each amplifier i and ground, and the capacitor between the input of each amplifier and ground are instead connected in parallel between the input of each amplifier and its corresponding output. A second technique employs a balanced impedance arrangement where, for example, a zero current with a non-zero thevenin conductance is achieved by employing equal valued
    T+ and Tij conductances.
  • Brief Description of the Drawing
    • FIG. 1 describes the prior art highly interconnected analog network;
    • FIG. 2 describes a network constructed in accordance with the virtual ground approach of our invention; and
    • FIG. 3 describes a network constructed in accordance with the balanced conductance approach of our invention.
    Detailed Description
  • The FIG. 1 circuit includes a capacitor and a resistor between each amplifier input and ground. The capacitor is the element that controls the time constant, or speed, of the circuit and in ordinary circuit it would behoove the designer to make the capacitor as small as practicable. The circuit of FIG. 1, however, permits feedback to be established through what effectively is a series connection of a number of amplifiers. Without any capacitance in the circuit, instability would almost certainly occur. Even with capacitance in the circuit an instability condition could result except that, with selection of the Tijconductances, stability is maintained.
  • There is an additional aspect to the presence of the capacitors. When the feedback paths to a particular capacitor of FIG. 1 are combined to appear as a single equivalent voltage and an equivalent resistance, Re, it becomes readily apparent that a pole exists in the frequency domain. That pole derives from the voltage division action of the capacitor and its parallel resistor, yielding a gain equation for each amplifier that is related to 1/(1 + sCRe). From this it is apparent that the pole position is a function of the feedback resistors and, therefore, we can expect different pole positions associated with different amplifiers in the FIG. 1 circuit. In turn, we should expect different speeds of response from the different amplifiers. What this means is that the circuit of FIG. 1 minimizes the energy function of Equation (2), but the manner in which it reaches this minimum is less than optimum since the slowest amplifier dictates the response time of the entire circuit.
  • In accordance with one aspect of my invention, the problem of different pole positions is obviated with the circuit of FIG. 2 where each capacitor (and its parallel resistor) is connected between its associated amplifier output and its negative input. The result is a virtual ground operation with an associated gain equation of R/Re(1 + sCR), where R is the resistor connected in parallel with the capacitor. That yields a fixed pole that is related solely to the capacitor and its parallel resistor. Correspondingly, the result is equal speeds of response to all of the amplifiers, and the fastest settling time of the circuit for a given capacitance value.
  • In accordance with another aspect of my invention, the problem of different pole positions is obviated with the circuit of FIG. 3. Therein, amplifier 10 is shown with input capacitor 11 and an input resistor 12 connected between the input of amplifier 10 and ground. Also connected to the input of amplifier 10 are conductance pairs
    Figure imgb0009
    , and
    Figure imgb0010
    derives its input from the output of amplifier i, and the output impedance of the amplifiers is assumed to be negligible.
  • The prior art computations of the T ij values yield either positive or negative Tij terms of different magnitudes. Since the amplifier input nodes are essentially at zero voltage potential, a negative Tijsimply means that current flows out of the amplifier's input node. A positive Tii means that current flows into the amplifier's input node. In the prior art, when a computed Tij is negative, the neural network of FIG. 1 incorporates a TTj element into the matrix. Correspondingly, when a computer Tij is positive, the neural network of FIG. 1 incorporates a T
    Figure imgb0011
    j element into the matrix. From this it can be seen that
    Figure imgb0012
    are disjoint; that is, either one or the other but not both appear at any one time.
  • In accordance with my invention, regardless of the required sign and magnitude of the computed Tij, both the
    Figure imgb0013
    conductances are included in the matrix, as shown in FIG. 3. The effective conductance presented to amplifier 10 by the conductance pair
    Figure imgb0014
    and that sum, in accordance with the principles of my invention, is arranged to be constant. Since that effective conductance is constant, e.g., K. the effective overall conductance presented at the input node of each amplifier is also constant, and that results in equal speeds of response for the amplifiers. On the other hand, the current that is actually flowing into each amplifier's input node must be different, as specified by the computed Tij, and that current is equal to
    Figure imgb0015
    . That value, e.g., +A, can be obtained while maintaining the requirement that (T
    Figure imgb0016
    + T
    Figure imgb0017
    ) = K by selecting the magnitude of T
    Figure imgb0018
    to be equal
    Figure imgb0019
    (K + A) by the magnitude of T
    Figure imgb0020
    to be equal
    Figure imgb0021
    (K - A).
  • To those skilled in the art to which this invention relates, many changes in embodiments and applications of the invention will suggest themselves without departing from the spirit and scope of the invention. For example, in situations where there are a large number of required zero currents flowing into the amplifier nodes, and it is more convenient to create conductances of magnitude K (rather than some value between K and 0), it may be useful to create T+ = Tj = K conductances at half of the amplifiers, and zero conductances at the other half of the amplifiers. In light of the above, the disclosures and the description herein are to be taken as purely illustrative, and not limiting in any sense.

Claims (7)

1. A network comprising:
a plurality of amplifiers Ai (10) each having an input node at which there is developed and input voltage Ui, and each developing a non-inverting output V; and an inverting output -V i, with both of said outputs being related to said input by a sigmoid function gi;
means for applying input current I i (101 ) to said input of each of said amplifiers Ai;
a conductance network for connecting said positive and negative outputs to said inputs, CHARACTERIZED IN THAT
said conductance network comprising conductance values selected for the nature of the decisional operation for which it is intended to minimize the energy function
Figure imgb0022
where V; and Vj are output voltages of said amplifiers Ai and Aj, respectively, Tij is a conductance that relates the amplified input voltage of amplifier Ai, having a gain function g(Ui), to the input node of amplifier Aj, Ri is the equivalent resistance at said input of said amplifier Ai,
and gi is the inverse of gi, and
means for equalizing the speed of response of said amplifiers.
2. The network of claim 1 wherein said means for equalizing comprises a subnetwork (FIG. 2) associated with each of said amplifiers and connected between the input and the negative output of each of said amplifiers.
3. The network of claim 2 wherein said subnetwork comprises a parallel interconnection of a resistor (32) and a capacitor (31).
4. The network of claim 1 wherein said means for equalizing includes the use of a conductance Tij with each conductance
Figure imgb0023
is a constant and
Figure imgb0024
is equal to said conductance Tij,
where T+ij is a conductance connected between output Vi of amplifier Ai and the input node of amplifier
Ajand Tij is a conductance connected between output -Vi of amplifier Ai and the input node of amplifier Ai.
5. The network of claim 1 wherein the means for said equalizing includes the use (FIG. 3) of conductances in said conductance network whose sum is essentially of a preselected value.
6. The network of claim 1 wherein said T
Figure imgb0025
j and said T
Figure imgb0026
j are always present in pairs.
7. The network of claim 1 wherein said T
Figure imgb0027
j and said T
Figure imgb0028
j are not disjoint.
EP87303018A 1986-04-14 1987-04-07 Parallel computation network Expired - Lifetime EP0242109B1 (en)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US06/851,239 US4731747A (en) 1986-04-14 1986-04-14 Highly parallel computation network with normalized speed of response
US851239 1986-04-14
SG26194A SG26194G (en) 1986-04-14 1994-02-21 Parallel computation network

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EP0242109A2 true EP0242109A2 (en) 1987-10-21
EP0242109A3 EP0242109A3 (en) 1989-01-11
EP0242109B1 EP0242109B1 (en) 1993-09-15

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EP (1) EP0242109B1 (en)
JP (1) JP2509615B2 (en)
CA (1) CA1258318A (en)
DE (1) DE3787396T2 (en)
ES (1) ES2042555T3 (en)
SG (1) SG26194G (en)

Cited By (1)

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Publication number Priority date Publication date Assignee Title
EP0382518A2 (en) * 1989-02-10 1990-08-16 Kabushiki Kaisha Toshiba Multi-feedback circuit apparatus

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US4858147A (en) * 1987-06-15 1989-08-15 Unisys Corporation Special purpose neurocomputer system for solving optimization problems
AU2485788A (en) * 1987-07-28 1989-03-01 Maxdem, Inc. Electrically settable resistance device
US4903226A (en) * 1987-08-27 1990-02-20 Yannis Tsividis Switched networks
US4875183A (en) * 1987-11-19 1989-10-17 American Telephone And Telegraph Company, At&T Bell Laboratories Neural networks
US4866645A (en) * 1987-12-23 1989-09-12 North American Philips Corporation Neural network with dynamic refresh capability
US4849925A (en) * 1988-01-15 1989-07-18 The United States Of America As Represented By The Secretary Of The Navy Maximum entropy deconvolver circuit based on neural net principles
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DE58906476D1 (en) * 1988-07-05 1994-02-03 Siemens Ag Digital neural network implemented in integrated circuit technology.
US4926064A (en) * 1988-07-22 1990-05-15 Syntonic Systems Inc. Sleep refreshed memory for neural network
US4943556A (en) * 1988-09-30 1990-07-24 The United States Of America As Represented By The Secretary Of The Navy Superconducting neural network computer and sensor array
US5093781A (en) * 1988-10-07 1992-03-03 Hughes Aircraft Company Cellular network assignment processor using minimum/maximum convergence technique
US4988891A (en) * 1989-05-09 1991-01-29 Mitsubishi Denki Kabushiki Kaisha Semiconductor neural network including photosensitive coupling elements
JPH02310666A (en) * 1989-05-25 1990-12-26 Mitsubishi Electric Corp Semiconductor neural circuit device
JPH04505678A (en) * 1989-06-02 1992-10-01 イー・アイ・デュポン・ドゥ・ヌムール・アンド・カンパニー Parallel distributed processing network featuring information storage matrix
US5113367A (en) * 1989-07-03 1992-05-12 The United States Of America As Represented By The Secretary Of The Navy Cross entropy deconvolver circuit adaptable to changing convolution functions
EP0411341A3 (en) * 1989-07-10 1992-05-13 Yozan Inc. Neural network
US5028810A (en) * 1989-07-13 1991-07-02 Intel Corporation Four quadrant synapse cell employing single column summing line
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US5130563A (en) * 1989-11-30 1992-07-14 Washington Research Foundation Optoelectronic sensory neural network
US5039870A (en) * 1990-05-21 1991-08-13 General Electric Company Weighted summation circuits having different-weight ranks of capacitive structures
US5039871A (en) * 1990-05-21 1991-08-13 General Electric Company Capacitive structures for weighted summation as used in neural nets
US5615305A (en) * 1990-11-08 1997-03-25 Hughes Missile Systems Company Neural processor element
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
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EP0382518A3 (en) * 1989-02-10 1991-01-09 Kabushiki Kaisha Toshiba Multi-feedback circuit apparatus

Also Published As

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CA1258318A (en) 1989-08-08
DE3787396D1 (en) 1993-10-21
ES2042555T3 (en) 1993-12-16
DE3787396T2 (en) 1994-02-24
JP2509615B2 (en) 1996-06-26
EP0242109A3 (en) 1989-01-11
US4731747A (en) 1988-03-15
JPS62296283A (en) 1987-12-23
SG26194G (en) 1995-03-17
EP0242109B1 (en) 1993-09-15

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